Artificial intelligence (AI) is playing a crucial role in work transformation. HR leaders must be thoughtful in determining how to harness its vast potential while managing the new risks that have arisen alongside it.
AI is revolutionizing the way we work, and the future of work is heavily dependent on its advancements. With the ability to analyze large amounts of data and perform routine tasks at lightning speed, AI streamlines repetitive and time-consuming tasks, freeing up employees to focus on more creative and value-added work. AI also enables better decision-making through data-driven insights, increasing efficiency and productivity in the workplace.
Moreover, AI is paving the way for new job opportunities and career paths in fields such as data science, machine learning and robotics.
Business leaders and policymakers increasingly recognize that AI adoption and use are key to economic competitiveness. How can HR most effectively and safely jump on this fast-moving train?
AI will have a significant impact on three HR pillars: people, process and technology:
People
HR systems and processes have given rise to a vast quantity of data about people, both business and personal. This data can help us predict future opportunities and challenges in managing talent, employee experience and preferences. In addition, generative AI can assist HR by creating a personalized and tailored experience for each employee. It can use data and insights gathered from previous interactions to better understand an employee’s preferences and needs, making HR processes more efficient and effective.
Process
AI will help HR and the business to evaluate the process flow and re-engineer the way we work. AI can simplify HR processes by automating routine tasks such as resume screening, scheduling interviews and onboarding new employees. There’s also a huge opportunity to use generative AI for personalized employee communications. For example, generative AI can help employees create personalized development plans to improve their skills.
Technology
AI as a technology and enabler will decrease and potentially even eliminate routine and repetitive tasks, unlocking employees’ capacities to focus on more strategic work. Gone are the days where HR professionals need to spend hours searching for benchmarks or cleaning data to provide a compelling business case.
HR needs to think big, start small and act fast when it comes to using AI in their work.
Our work with a utility company shows how AI is changing skill requirements. They have a 600-person customer service team that historically relied on simple scripts to handle billing inquiries. But as AI chatbots resolve basic issues, the role of its agents has changed.
Reps now need more problem-solving abilities, empathy and understanding of the broader business context to build strong customer relationships. The company realized they may need to provide training on new skills such as up- and cross-selling, broader technical know-how to be able to answer more complex queries and a better understanding of cultural references. They also changed their approach to recruiting and compensating these roles. It’s a prime example of how AI is raising the bar on the core competencies people need.
Given AI’s incredible and far-reaching potential, it can be difficult to home in on the best ways to use it in your organization. Determining your most critical needs and defining the right opportunities are key to deciding which AI solutions to use. Start by asking simple questions:
Depending on the answers to the questions above, HR leaders will need to consider various risks and other considerations when deciding to adopt AI into their work.
Bias: AI comes with its own risks of perpetuating bias and giving false information. Unchecked, it can create as many problems as it solves, which is why organizations must establish proper governance. At the core of your AI governance should be people who review outputs and decisions.
One of the earliest HR applications of AI was resume screening, using machine learning to filter large applicant pools. In using these solutions, many employers found that the algorithms perpetuated bias present in the historical hiring data that was used to train the AI. Removing identifying information like names and addresses can help, but the key is carefully examining training data for bias in the first place. The quality of data used to train algorithms is key, and the data sets need to be truly representative. If the training data contains inherent bias, the algorithm will perpetuate that bias.
Privacy and data ownership: Another issue is privacy. HR deals with highly sensitive employee information like health records, employment history and performance data. It's critical that employee privacy remains protected, and data is used ethically. Deciding what data is used for what purpose, ensuring its accuracy and considering questions of data ownership and consent, must be carefully considered. Especially since large language models are being trained on internet data without always having explicit permission, the issues of data rights in AI are becoming hotly debated.
Generated content: In addition to data issues, we must grapple with risks around generated content powered by AI including deep fakes, manipulated data logs and AI hallucination (when generative AI uses incorrect data to create inaccurate or misleading content). Companies need safeguards to verify the accuracy of information, and ways to prevent and detect malicious uses of synthetic media or falsified records that an AI has created. We don’t yet have robust guardrails in these areas.
The IT function will need to play a key role in implementing technical and governance measures to mitigate these risks as AI scales across the organization. Early trends indicate that there is greater risk of security breaches when organizations use large language and other AI models. Cybersecurity teams in the IT function are being required to develop and update their safeguards, as companies pilot AI models in different parts of their business.
Chief human resource officers should work with their technology leaders to determine how much human oversight is needed and how to secure AI systems. Most AI algorithms are black boxes, making it hard to explain how it draws conclusions and makes recommendations. It’s particularly important to maintain human oversight when making people decisions such as shortlisting, hiring and promotions.
When leaders establish the proper governance to reduce risks, HR can embrace the power of AI to drive efficiency and value. The key is combining machine intelligence for optimization, pattern-finding and prediction with human judgment to train, interpret and apply AI outputs in the proper context. When used this way, AI can be a tremendous asset in improving HR processes from recruiting and leveling to benchmarking and beyond.
The HR function has a tremendous opportunity to lead the way in scaling AI’s positive impact, helping improve business outcomes and enabling career growth for employees.
